Óscar Martínez Mozos, Cyrill Stachniss, Wolfram Burgard.
Supervised Learning of Places from Range Data using AdaBoost.
In Proc. of the IEEE International Conference on Robotics and Automation (ICRA).
pp. 1742-1747. ISBN: 0-7803-8915-8.
Barcelona, Spain. April, 2005.

Finalist: ICRA Best Student Paper    Certificate  Photo
Link to IEEE RAS news]


This paper addresses the problem of classifying places in the environment of a mobile robot into semantic categories. We believe that semantic information about the type of place improves the capabilities of a mobile robot in various domains including localization, path-planning, or human-robot interaction. Our approach uses AdaBoost, a supervised learning algorithm, to train a set of classifiers for place recognition based on laser range data. In this paper we describe how this approach can be applied to distinguish between rooms, corridors, doorways, and hallways. Experimental results obtained in simulation and with real robots demonstrate the effectiveness of our approach in various environments.

Paper: [pdf: 392k]


  title     =   {Supervised Learning of Places from Range Data using AdaBoost},
  author    =   {Oscar Martinez Mozos and Cyrill Stachniss and Wolfram Burgard},
  booktitle =   {Proceedings of the IEEE International Conference on Robotics and Automation},
  year      =   {2005},
  pages     =	{1742--1747},
  address   =   {Barcelona, Spain},
  url 		=	{http://www.informatik.uni-freiburg.de/~omartine/publications/martinez2005icra.pdf}	


Online classification with a mobile robot.
See how places are classified and colored as the robot moves.
Colors: room(blue), corridor(red), doorway(yellow).
Video: [avi: 77k].